{"id":"https://openalex.org/W3015578900","doi":"https://doi.org/10.1109/icassp40776.2020.9053119","title":"SDTCN: Similarity Driven Transmission Computing Network for Image Dehazing","display_name":"SDTCN: Similarity Driven Transmission Computing Network for Image Dehazing","publication_year":2020,"publication_date":"2020-04-09","ids":{"openalex":"https://openalex.org/W3015578900","doi":"https://doi.org/10.1109/icassp40776.2020.9053119","mag":"3015578900"},"language":"en","primary_location":{"id":"doi:10.1109/icassp40776.2020.9053119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087779583","display_name":"Libao Zhang","orcid":"https://orcid.org/0000-0002-0888-2330"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Libao Zhang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101903923","display_name":"Shan Wang","orcid":"https://orcid.org/0000-0001-6243-956X"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shan Wang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100354377","display_name":"Xiaohan Wang","orcid":"https://orcid.org/0000-0001-6206-7911"},"institutions":[{"id":"https://openalex.org/I25254941","display_name":"Beijing Normal University","ror":"https://ror.org/022k4wk35","country_code":"CN","type":"education","lineage":["https://openalex.org/I25254941"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohan Wang","raw_affiliation_strings":["School of Artificial Intelligence, Beijing Normal University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing Normal University, Beijing, China","institution_ids":["https://openalex.org/I25254941"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087779583"],"corresponding_institution_ids":["https://openalex.org/I25254941"],"apc_list":null,"apc_paid":null,"fwci":0.4885,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.64635007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"33","issue":null,"first_page":"2653","last_page":"2657"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9944999814033508,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9926000237464905,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.828357458114624},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7538009285926819},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.7205197811126709},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.7179490327835083},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6658210754394531},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5409018397331238},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5313392877578735},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.49519816040992737},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46615278720855713},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4592532813549042},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.45634257793426514},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3543132543563843},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.07090428471565247}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.828357458114624},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7538009285926819},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.7205197811126709},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.7179490327835083},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6658210754394531},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5409018397331238},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5313392877578735},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.49519816040992737},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46615278720855713},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4592532813549042},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.45634257793426514},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3543132543563843},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.07090428471565247},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp40776.2020.9053119","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp40776.2020.9053119","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.550000011920929,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W2028763589","https://openalex.org/W2065002911","https://openalex.org/W2081418206","https://openalex.org/W2097900287","https://openalex.org/W2128254161","https://openalex.org/W2133496072","https://openalex.org/W2145023731","https://openalex.org/W2156936307","https://openalex.org/W2256362396","https://openalex.org/W2395611524","https://openalex.org/W2519481857","https://openalex.org/W2560622558","https://openalex.org/W2746139371","https://openalex.org/W2767248074","https://openalex.org/W2767516232","https://openalex.org/W2779176852","https://openalex.org/W2891358983","https://openalex.org/W2894938704","https://openalex.org/W2897177665","https://openalex.org/W2949922688","https://openalex.org/W2955731188","https://openalex.org/W2962754725","https://openalex.org/W2963306157","https://openalex.org/W2963928582","https://openalex.org/W3100761169","https://openalex.org/W3103309903","https://openalex.org/W4241071816","https://openalex.org/W6679820939"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W2522537526","https://openalex.org/W4308659218","https://openalex.org/W2998228095","https://openalex.org/W2791535170","https://openalex.org/W2001271057","https://openalex.org/W2468641972","https://openalex.org/W1586536980","https://openalex.org/W2627333571","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Transmission":[0],"similarity":[1,38],"is":[2,23,46,95,116],"an":[3],"important":[4],"feature":[5],"which":[6,126],"can":[7,75,127],"greatly":[8,78],"increase":[9],"the":[10,49,64,85,120,129,138,142],"capability":[11],"of":[12,51,131],"convolutional":[13,93],"neural":[14],"network":[15,42,94],"(CNN)":[16],"to":[17,62,97],"fit":[18],"transmission":[19,40,52,65,121],"map.":[20],"However,":[21],"it":[22],"not":[24,76],"sufficiently":[25],"utilized":[26],"in":[27,101],"existing":[28],"algorithms.":[29],"In":[30],"this":[31],"paper,":[32],"we":[33,55],"propose":[34],"a":[35,57,91,111],"novel":[36],"light-weight":[37],"driven":[39],"computing":[41,80],"called":[43],"SDTCN":[44],"that":[45,137],"guided":[47],"by":[48,124],"attributes":[50],"similarity.":[53,66],"First,":[54],"adopt":[56],"non-data-driven":[58],"image":[59],"segmentation":[60,71],"method":[61,74],"acquire":[63],"Compared":[67],"with":[68],"CNN":[69],"based":[70],"approaches,":[72],"our":[73],"only":[77],"save":[79],"resources,":[81],"but":[82],"also":[83],"separate":[84],"objects":[86],"and":[87,147],"background":[88],"precisely.":[89],"Second,":[90],"full":[92],"introduced":[96],"reduce":[98],"blocky":[99],"effects":[100],"SDTCN.":[102],"Finally,":[103],"unlike":[104],"previous":[105],"\"first":[106],"airlight":[107,113,132],"then":[108],"transmission\"":[109],"mode,":[110],"dependable":[112],"estimation":[114],"approach":[115],"designed":[117],"drawing":[118],"on":[119,145],"map":[122],"generated":[123],"SDTCN,":[125],"improve":[128],"accuracy":[130],"effectively.":[133],"Extensive":[134],"experiments":[135],"demonstrate":[136],"proposed":[139],"algorithm":[140],"outperforms":[141],"state-of-the-art":[143],"methods":[144],"synthetic":[146],"real-world":[148],"images.":[149]},"counts_by_year":[{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
